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Minimum Experience: 2 years of process engineering experience in a chemical or petrochemical environment; with at least 2 years of experience using timeseries tools such as SEEQ, natural language processing (NLP), building predictive maintenance machine learning productions and taking them to production, building machine learning solutions with cloud tools (AWS, Azure, Google cloud), and knowledge of applying overall equipment effectiveness (OEE) calculations.
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Warehousing: Experience in Snowflake Data Cloud, SQL Server, Azure, AWS Redshift, Google Big Query. Science & programming: Python, R, SQL, SAS, Java or similar Lower Priority. Data Architect who will closely work with Business Analysts in-order to design and develop the One-BI data warehouse which will be used as Enterprise-wide reporting system.
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Forensic science programs must be either FEPAC-accredited OR meet the minimum curriculum requirements pertaining to natural science core courses and specialized science courses set forth in the FEPAC Accreditation Standards.
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With one of the largest multimedia air and land permitting and compliance teams in the country, we support client success in manufacturing and industry, liquids delivery and processing, natural gas storage and delivery, power generation and delivery, and transportation projects.
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This internship will offer the successful candidate the opportunity to develop an understanding of the Oil & Gas industry and advanced Information Technology applications not limited to but including areas such as High Performance Computing, Data Management, Data Analysis, Data Science, Application Development, Cloud Computing, Infrastructure deployment and management and IT Process & Governance.
InternExpandApply NowActive JobUpdated 14 days ago - UpvoteDownvoteShare Job
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Net Developer responsible for energy trading and risk management systems, market data information, and other systems and processes required to support natural gas trading. The areas of expertise must include physical and financial deals, scheduling, risk reporting, P&L, and market data for Natural Gas and Client commodities.
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Bachelor's or Master's degree in wildlife biology, rangeland ecology, environmental science, forestry, botany, soil science, or a closely related natural resource field preferred.
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3+ years of experience with Natural Language Processing (NLP) and Large Language Models (LLM) 3+ years of experience building and maintaining scalable API solutions. Additionally, the Generative AI Engineer will participate in a wide variety of Natural Language Processing activities, including refining and optimizing prompts to improve the outcome of Large Language Models (LLMs), and code and design review.
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Bachelor’s degree from an accredited university in Mathematics, Statistics, Data Science, Quantitative Analysis with at least three years of full-time experience in program evaluation, educational research, or other social science research; or.
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Deep understanding of deep learning architecture, machine learning, natural language processing (NLP), and generative models. Master's degree in Computer Science, Data Science, Machine Learning, or a related field with a strong focus on Artificial Intelligence.
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Data Visualization: Effective data visualization skills for time series and geospatial data. Improve and develop products for US ISO markets' quantitative models, including data handling and processing.
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If you are selected as the Natural Gas Scheduler, you will need to be able to work in an open, fast-paced environment with daily time deadlines and heavy workloads. Must be legally authorized to work in the United States on a full-time basis for anyone other than current employer.
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Proficient in at least one analytical programming language relevant for data science. Python ecosystem preferred, R will be acceptable, machine learning libraries & frameworks (e.g. TensorFlow, PyTorch, scikit-learn) and familiar with data processing and visualization tools (e.g., SQL, Tableau, Power BI.
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BS/BA degree in natural science field of study required. This is a full-time (60 hours/week), limited-term role with a duration of 10-12 weeks. Data entry, data review, and GPS use.
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A master’s degree or PhD in Computer Science, Statistics, Applied Mathematics, or a related field, with at least 5 – 7 years’ experience in data science or a similar role. We're look for a Lead Data Scientist to spearhead the design, development, implementation and maintenance and improvement of advanced data science initiatives across business units, directly aligning with strategic objectives.
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big data science full time natural language processing jobs in Houston, TX
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